Researchers in the Building Technology & Urban Systems Division (BTUS) at Lawrence Berkeley National Laboratory develop data and technologies that increase energy efficiency and improve the health, safety and comfort of building occupants, in the United States and worldwide.

We work closely with industry partners, academics and government officials to achieve these goals, and share our research widely.

We offer a variety of technologies designed to simulate and model real-world circumstances to assist in energy-saving programs and help building owners build better buildings. These tools can help calculate performance of building systems like windows and shades, help consumers and builders pick the best windows for a variety of applications and much more.

Publication Type

Date Published

Authors

LBNL Report Number

LBNL-55087

Abstract

Machine to Machine (M2M) is a term used to describe the technologies that enable computers, embedded processors, smart sensors, actuators and mobile devices to communicate with one another, take measurements and make decisions — often without human intervention.

M2M technology was applied to five commercial buildings in a test. The goal was to reduce electric demand when a remote price signal rose above a predetermine price. In this system, a variable price signal was generated from a single source on the Internet and distributed using the meta-language, XML (Extensible Markup Language). Each of five commercial building sites monitored the common price signal and automatically shed site-specific electric loads when the price increased above predetermined thresholds. Other than price signal scheduling, which was set up in advance by the project researchers, the system was designed to operate without human intervention during the two-week test period.

Although the buildings responded to the same price signal, the communication infrastructures used at each building were substantially different. This study provides an overview of the technologies used at each building site, the price generator/server, and each link in between. Network architecture, security, data visualization and site-specific system features are characterized.

The results of the test are discussed, including: functionality at each site, measurement and verification techniques, and feedback from energy managers and building operators. Lessons learned from the test and potential implications for widespread rollout are provided.